The motion of cardiac tissues can be assessed by viewing medical images of the cardiac tissues, using one or more different 2D and 3D imaging modes (in particular tagged or untagged cardiac MRI, and/or different modes of ultrasound imaging). From such dynamic imaging, one can extract tissue velocity, strain and/or strain-rates. Such strain and strain rates can be visualized using parametric images, wherein the intensities associated with positions represent parameter values, such as strain or strain rate. Such parametric imaging techniques can provide valuable diagnostic information relating, among others, to hypokinesy, akinesy, diskinesy of certain part of the myocard, or myocardial asynchronism. However, the validity of this parametric imaging may depend on the image contrast and on the accuracy of the estimated motion field.
Ledesma-Carbayo, M. J. Santos, A. Kybic, J. Mahia-Casado, P. Garcia-Fernandez, M. A. Malpica, N. Perez-David, E. Desco, M.; “Myocardial strain analysis of echocardiographic sequences using nonrigid registration”; Computers in Cardiology, September 2004, pp 313-316 (hereinafter: Ledesma-Carbayo et al.), describe a way of assessing the extracted motion field accuracy. Using the extracted motion field, a motion-compensated image sequence is generated in such a manner that all images in the sequence are made similar to a selected reference frame. Usually, the reference frame is selected among end-diastolic frames.
Techniques for visualizing a cardiac image are known, for example using direct volume rendering or multi-planar reformat. However, these visualizations do not provide an efficient way to inspect the myocardium in detail.